Medical Ethics in Artificial Intelligence

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Question 1 of 9

1. Question
- Ethics around the creation of an AI solution needs to consider the three aspects of its development:
  - Data
  - Model development
  - Model Deployment and Monitoring
- For each aspect the four pillars of medical ethics need to be considered except:
- Autonomy
- Beneficience
- Non-Maleficience
- Efficacy
- Justice
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Question 2 of 9

2. Question
Doing ethics in Artificial Intelligence is essential to shape AI in health. It is merely a tool, which neither good nor bad. Which of these statements is incorrect ?
- AI solutions and data can profit individuals which can harm patients, groups and the social good.
- One of the big arguments of AI in health is that it reduces costs
- Healthcare providers can also influence technology based solutions using AI.
- Ethical debates are primarily public health and technological questions.
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Question 3 of 9

3. Question
There are several areas in an AI-based solution where medical solutions can be applied. Which of them ?
- The Data
- The process of development
- The deployment of models and systems in clinical practice.
- All of the above
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Question 4 of 9

4. Question
Data is the New oil…at it is even more important when it comes to protect our intimacy, especially when it comes to pictures on our skin.

Which of the following problems need to be addressed ?
- Privacy
- Consent
- Patient awareness of their own data
- Ownership of the data
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Question 5 of 9

5. Question
Of the 4 pillars of medical ethics beneficience and non-maleficience are two of them. Which statements concerning them is correct.
- Confidentiality loss for one individual can be for the benefit of a collective AI derived solution.
- Anonymization when done well, always prevents re-identification.
- Beneficience for the collective can be justified in some circumstances such as a lack of resources.
- Non Maleficience is limited to privacy and confidentiality concerns.
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Question 6 of 9

6. Question
Consent is essential before collecting data, and it a big investment which explains why informed consent taking is typically made right at the beginning. Which of the following statements is correct ?
- Opt-out informs how collected data is processed. The patient can have his/her data removed by requesting it.
- The NHS has been using an opt-out model concerning patient data.
- Opt-in consent is always taken before patient data is collected.
- Opt-out at the NHS is possible only up to one year after the data has been submitted.
- All of the above statements are correct.
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Question 7 of 9

7. Question
According to researchers from Stanford university researching the framework of public data, the following is a conclusion for use of data as a public good:
- If the clinical data is really not owned by anyone, those who interact with it then have an obligation to ensure that the data is used for the benefit of future patients in societies.
- This data should be widely shared for research and development, and all the individuals and entities with access to that data, then essentially become stewards of that data and become responsible to carefully safeguard the privacy and to ensure that the data is used for developing knowledge and tools for the good.
- Algorithms developed on the data should be shared.
- Patient consent wouldn’t necessarily be required before the data is used for secondary purposes, such as AI development and training and testing, as long as there are mechanisms in place to ensure that ethical standards are being followed.
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Question 8 of 9

8. Question
Conerning the data, which of the following statement is true concerning the potential bias using AI tools ?
- Biases in data can always be corrected using AI algorithms.
- Epidemiology is the only factor important in determining the representativity of a datase.
- None of the above.
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Question 9 of 9

9. Question
When it comes to health solutions using AI, which of the following statements is true ?
- Data if representative, always leads to a working algorithm.
- Algorithms solutions are always explainable.
- Convoluted neural networks contribute to the so-called "Black Box" concept.
- Transparency in health solutions using AI is not as important as in AI solutions in law.
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Medical Ethics in Artificial Intelligence

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